Adaptive Coding and Modulation for Next Generation ...

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20th AIAA International Communication Satellite Systems Conference and Exhibit Coding and Modulation for Next Generation 12-15 May 2002,Adaptive Montreal, Quebec, Canada

AIAA 2002-1863 Broadband Multimedia Systems

Riccardo De Gaudenzi, Rita Rinaldo  European Space Agency ESTEC, Keplerlaan 1, 2200 AG Noordwijk, The Netherlands

Downloaded by Thomas Butash on February 1, 2013 | http://arc.aiaa.org | DOI: 10.2514/6.2002-1863

This paper investigates the potential advantages provided by adaptive coding and modulation (ACM) for next generation broadband satellite communication systems operating at Ka-band and above. The problem tackled in the manuscript is how to find an optimal physical layer structure able to efficiently support packet type of traffic and to adapt to the varying propagation channel conditions and location dependent signal-tointerference plus noise ratio (SNIR). In particular, the physical layer and key system parameters optimization problem (i.e. coding rate, modulation order, spreading factor, frequency and polarization reuse factors) is tackled for the general case of the downlink of a multibeam satellite system. Eventually, the average system capacity and bit rate distribution for the proposed adaptive coded modulation scheme is derived in a realistic scenario with different frequency reuse factors. The resulting large capacity advantage with respect to solutions currently envisioned for satellite multimedia systems is proved.

Introduction Multimedia satellite systems operating at high frequency bands (e.g. Ka band corresponding to 20-30 GHz) have to take into account link degradation due to severe atmospheric propagation losses. 1 The approach followed by multimedia systems under development 2 is the allocation of a fixed TDM downlink stream bit rate and power margin computed according to the required link availability over the covered region. This results in a worst-case dimensioned system in which precious satellite power resources are wasted when as it is often the case the link atmospheric fading is negligible. New approaches are emerging to solve the problem of efficiently supporting highly bursty traffic on the downlink of third-generation mobile wireless communication systems. 3 The following paper, inspired by recent terrestrial ACM developments for wireless networks, investigates their applicability and potential advantages for the next generation satellite broadband networks. Despite the fact that ACM has been analyzed at the physical layer level,4 to the author’s knowledge no comprehensive capacity analysis advantages in a realistic satellite environment have been published so far. In the proposed ACM approach, to ease resource allocation the downlink TDM carrier power as well as the occupied bandwidth are fixed, but the bit rate is changed on a slot by slot basis, according to the estimated link  Communication Systems Section, Electrical Engineering Department, Directorate of Technical and Operational Support, email:[email protected], [email protected]

Copyright c 1999 by the American Institute of Aeronautics and Astronautics, Inc. No copyright is asserted in the United States under Title 17, U.S. Code. The U.S. Government has a royalty-free license to exercise all rights under the copyright claimed herein for Governmental Purposes. All other rights are reserved by the copyright owner.

channel quality. This is possible through adaptation of physical layer parameters as coding rate and modulation order. This approach consisting in adapting physical layer but not satellite carrier power has been recently shown to be quasi-optimal from the information theory viewpoint. 5 As the TDM carrier power and bandwidth is constant, the downlink interference within the satellite coverage is constant as well, independently from the overall beam capacity variations taking place to adapt to time-varying propagation conditions. It is important to remark that other link adaptation strategies causing power and bandwidth variations on a slot-by-slot basis are not effective in the presence of very bursty traffic. This is because the satellite intrinsic propagation latency prevents from any fast closed-loop adaptation technique which may be pursued by terrestrial wireless networks. In the following an optimization of the physical layer parameters allowing the rate adaptation is performed in order to achieve the highest link spectral efficiency. The optimisation process results and the cumulative fading distribution are used to derive the average ACM system capacity.

System assumptions In the following we focus on the forward link of a pointto-point multi-beam satellite communication system, covering a region partitioned over N b beams. A geostationary satellite orbit is assumed as it represents the worst-case propagation delay which can be encountered. For the following discussion the focus will be on the satellite to terminal link thus it is inessential if a regenerative or bent-pipe satellite is considered. In case of a transparent system a few terrestrial gateways are needed to serve the user terminals in the coverage, since each gateway can serve a large

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number of satellite beams. The necessary processing to perform adaptive coding and modulation will take place in the gateways. On the contrary, in case of a fully regenerative system we can assume the processing co-located at the satellite. In both cases the carriers will be organized in a hybrid Time Division Multiplexing/Frequency Division Multiplexing (TDM/FDM) scheme; in the following we will consider for simplicity only one carrier for each down-link beam. Channel quality estimate variations is reported as small packets by the active user terminals (UT) through the satellite repeater to the gateway station in the transparent case or directly to the satellite in the regenerative case. The UT SNIR reports allow to match the individual ACM slot physical layer to its current channel conditions. Since it is known that under typical rain fading phenomena the fading rate at Ka-band is generally in the order of few tenths of dB/sec, SNIR variations in presence of rain can be tracked by the UT reporting system and followed by the satellite long loop physical layer adaptation system. The UT SNIR reports are not required with constant periodicity. To the purpose of tracking the ”slow” propagation conditions variations it is sufficient that each active UT provides a new SNIR report only when a variation exceeding a given threshold (compared to the previous estimate reported) is detected. In this way the network can efficiently react to propagation conditions modifications with minimum signaling overhead. We assume that the downlink TDM carrier is organized in frames of duration T F sub-divided in regular time slots of duration T SLOT with Nc TSLOT Rc chips, being R c the chip rate. A user packet is formed by a variable number NS of slots depending on the data rate supported by the UT link. In each slot N PIL chips are dedicated to the so called pilot channel which is used to synchronize all UTs within the same beam; further N MAC chips are dedicated to the medium access control. If N PR is the number of chips per packet occupied by the preamble containing physical layer format information, the number N PAY of data payload chips in a packet can be computed as:

=

NPAY

= N N c

S

NPR

NS  NPIL

NS  NMAC (1)

The input traffic buffering, scheduling, segmentation, and allocation to available physical layer slots is part of the upper layers and is not discussed in this paper. In the proposed system configuration of an adaptive physical layer with variable coding rates and modulation order it is evident that some kind of coded signal spreading is required.

The above discussed modulator functional block diagram is summarized in Fig. 1. In the following we focus our analysis on the payload part of the downlink signal thus neglecting the common signaling and pilot signal. Fig. 2 represents a simplified version of the previously described general ACM modulator functional block diagram. The slot input information bit stream at bit rate R b is first coded1 0 0 at rate r n=m, then the resulting data R bE Rb =r rate is matched to the following M-ary modulator input data rate RbM by repetition and puncturing (R bM P R RbE ). For 0 simplicity we define the overall coding rate as r r =P . The interleaver between the rate adaptation block and the M-ary modulator is used to decorrelate at the demodulator side noise samples affecting a M-ary symbol according to the Block Interleaved Coded Modulation (BICM) principle.6 It is in fact very important to reuse a single coder/decoder unit for various modulation formats. With this respect the BICM approach appears to be the right solution and allows to achieve near-optimum results 2 reusing the same coder/decoder for different M-ary modulation schemes. Also to alleviate the problem of satellite High Power Amplifier (HPA) nonlinear characteristic the use of APSK M-ary modulations 7 is envisaged. The M-ary modulator I-Q channel symbol rate R s M Rb = 2 M is then scrambled by the I-Q scrambling/spreading sequences at rate R c with spreading factor Rc =Rs L  , L integer. We refer to scrambling when the X-ored sequence has the same chip rate as the coded I) while spreading occurs when Q stream (Rs Rc , L L> . In order to ensure the interbeam co-channel interference isolation the I-Q scrambling/spreading sequences are assumed unique for each downlink TDM carrier belonging to a specific beam. To improve the physical layer robustness to phase errors they are different (thus quasi-orthogonal) TF for the I and Q channels and have a period T SCR corresponding to N SCR Rc TF chips.

=

=

=

=

=

log

=

1

1

=

=1

=

=

Capacity estimation We assume that the propagation channel atmospheric attenuation a x; y is having the same pdf p A a for all the coverage locations and it is spatially uncorrelated, so that the fading in x; y is independent from the one present in adjacent locations.

( )

()

( )

1 Each

slot is terminated by tail bits resetting the encoder. originally proposed for the fading channel BICM was shown to be close to optimum also over the AWGN channel of interest here.8 2 Although

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I-Q SPREADING/ SCRAMBLING

RATE PARAMETERS CONTROL

TIME MULTIPLEXER

PILOT/SIGNALING MODULATOR

BUFFER MULTIPLEXER

INPUT CHAN

RATE CONTROL

cos ω t

RATE

VARIABLE RATE ENCODER

FRAME FORMATTER

M-ARY MODULATOR

-sin ω t S/P INTERL

MATCHING

CONVERT

SPREADING SEQUENCE GENERATOR

Fig. 1 Adaptive Coding and Modulation modulator functional block diagram. Rs

Rb

VARIABLE RATE ENCODER

RATE MATCHING E Rb

S/P CONVERT

INTERL RM b

M Rb

M Rb log M

r’

I-Q SPREADING/ SCRAMBLING

INFORMATION BITS

M-ARY MODULATOR

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INPUT

cos ω t

Rc

Rs

2

SPREADING -sin ω t SEQUENCE GENERATOR L

Fig. 2 Adaptive Coding and Modulation simplified modulator block diagram.

Since the bit rate is dependent on user location and channel conditions the optimization of the physical layer parameters is performed on each link, that is for each location x; y in the coverage and for each value of the fading attenuation random variable.

parameters. The link efficiency can be computed as:

^(

( )

 s x; y; a x; y ; Np ; fR

( )

) =

max r;M;L;R h

smax

1 = Nmax p ;fR Nb ZZ

(x;y )2B

^(

s x; y; Np ; fR

) =

Z 0

n

Nb X n=1

^(

(

)



s x; y; Np ; fR dxdy

^(

( )

where Nb is the number of beams in the satellite coverage, S  the function measure of the surface and the system parameters fR  and Np  , respectively frequency and polarization reuse factors. The parameter optimization process is therefore performed in two separate steps, first physical layer and then frequency and polarization reuse

1

1

)

)

=4 r log M (5) 4 t = L (6) By observing that s=t = R =R and assuming the operat2

R

) ()

 s x; y; a x; y ; Np ; fR pA a da (3)

()

( )

)

s

(2) 1

j

where r; M; L; R are the parameters described in the previous section and  req r; M is the required E b =Nt , function of coding rate and modulation order. Let define:

1

S (Bn )

( (

Rb Np fR Rc

Eb x; y; a x; y ; Np ; fR Nt (4)  req r; M g

We can then derive the average system efficiency: (

i



b

c

ing point req function of s rather than separately of r and M we finally get:

^(

 s Np ; fR

) = max s;t



sNp tfR

  (s)g

j st

h

Ec Nt

req

i

(x; y; a(x; y); fR ; Np ) (7)

Assuming that the Gaussian approximation holds true for

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the co-channel inteference 3, the SNIR in each coverage location x; y with the propagation fading r.v. a x; y can be expressed as:

( )

( )

(

( ) ( )( ) [ ( )] + ( ( )

( ) ( ) [ ( )] ( ( )

^s (Ec =Nt ) =

)g

( ) = N (a(x; y )) =

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C cs x; y

( ) ( ) +  (1 ( ))

PSAT N0cs

0

GSAT x; y GRX Lp x; y N0 a x; y

(

( )

I0 x; y; a x; y ; fR ; Np

[

](

)=

( ) ( ) +I ( )

C cs x; y a x; y   Rc CI x; y; fR

pol 0

(

I0pol

= 0

cs (x;y )a(x

n;yn )

c (Np

1)Xpol

R

if Np if Np

=2 =1

(12)

with Xpol as the interference cross-polarization factor. The optimization methodology for the equation (7) is detailed in the following section. The outage probability can be computed by introducing a limitation in the minimum bit rate supported by the physical layer R bmin so that: Pout 3 The

= Pr

2C

(x;y )



( )R

Rb x; y

min

b



req

(14)

req

()  0  (s) = 2 s1

1

s

t Ec s Nt

(15)

( )

=  (s)

(16)

req

=1 ) 1

. Since t  t1 In the present case it can be assumed t 1 it follows from (16) that s req s = Ec =Nt  . Let s be Ec =Nt and smin the solution of the equation s req s fs1 ; sg. In the case t  t2 it follows sreq s = Ec =Nt  t2 . Let s be the solution of the equation s req s t2 Ec =Nt and smax fs2 ; sg. The highest efficiency is obtained when s s min and t smin req smin = Ec =Nt :

()( ( )=

max

=

=

()( ) ()=

= min

(

)(

^(

 s Ec =Nt

(11)

)

C

j

()

(10)

where C=I x; y; fR is the satellite antenna C=I at location x; y in case of frequency reuse factor f R computed as difference between antenna gains of the useful and interfering beams and

( )

  (s)

o

Let start observing that  req s is a non decreasing function of s. We can assume that  req s follows the Shannon bound with an impairment factor , <  < so that:

(9)

( )

( )

t Ec s Nt

i

sNp tfR

The maximum of s=t can be found among the points s; t satisfying the following relation:

where PSAT is the satellite total beam RF power, Lp x; y the satellite-to-user path loss, G RX the receiver antenna gain, G SAT x; y the satellite antenna gain to location x; y . An explanation of the noise power spectral density degradation due to fading takes place in the appendix. The interference power spectral density can be obtained as:

( )

max

(8)

)



(s;t); s1 ss2 ; t1 tt2

h

where C cs x; y is the clear-sky received power at location x; y , N0 a x; y the noise power spectral density at the receiver and I 0 x; y; a x; y ; fR ; Np the interference power spectral density at location x; y . The following relations hold:

( )

In order to achieve the highest system capacity the following optimization problem needs to be solved:

)=

Ec x; y; a x; y ; fR ; Np Nt cs C x; y a x; y Rc fN0 a x; y I0 x; y; a x; y ; fR ; Np

=

Capacity Equation Optimization

=

)

)=

h

i

c Np Nt req smin fR E

(

)

(17)

If smin > smax than the highest efficiency is obtained s Np and is equal to max . for s smax and t fR The theoretical spectral efficiency obtained following this approach by means of an infinite continuous set of coded modulation formats is presented in Fig. 3; it has : , which corbeen assumed the impairment factor  responds to 3 dB distance from the Shannon bound. It is worth noting that although in principle we can make Fig. 3 endless growing with E c =Nt for the current evaluation we limited M to 64 and r  = . In practice, the achievable modem performance distance from the Shannon bound may be less for M  and higher for M  . The proposed 3 dB degradation figure represents a good average value.

=

=1

 =05 78

8

16

Numerical results (13)

conjecture has been supported by detailed physical layer simulations taking into account coding, band-limiting and channel spreading.

Multibeam Satellite Study Case In order to assess the effective advantage provided by ACM in the forward link of a broadband satellite system

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6

Parameter

Value

Satellite orbit

GEO

Carrier frequency

20.0 GHz

Total bandwidth (R c )

500 MHz

Fading profile

As for Capua (I) (see Fig.6)

Satellite antenna beams

169

Antenna peak gain

54.3 dBi

Antenna efficiency

100 %

Frequency reuse factor (f R )

1, 3, 4

Polarization reuse factor (N p )

1

RF power/beam

5 20 dBW

Outage requirement (P out )

99.5 % EOC

Receiver antenna gain

42.14 dBi

Clear sky receiver temp. (T CS )

231.35 K

spectral efficiency (bit/sec/Hz)

5

4

3

2

1

0 −20

−15

−10

−5

0 Ec/Nt (dB)

5

10

15

20

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Fig. 3 ACM theoretical efficiency.

a study case has been considered with the set of system parameters summarized in Table 1. The satellite beam footprint is shown in Fig. 4. No effort has been devoted to the coverage optimization of dry lands. The antenna has been



Receiver rain delta temp. ( T 0 )

Fig. 4 GEO 169 beams satellite antenna footprint.

simulated assuming the following ideal individual beam antenna pattern:

Table 1 Study case system parameters



(p + 1)(1 T ) J () F (u; v ) = (p + 1)(1 T ) + T 2  +  T J ()  + 2 p! 1 T p

227 K

1

+1

+1 +1

pwhere u; v

(18)

=

are the satellite antenna co-ordinates,  and the following parameters have been considered: T ,p : . The beam centers have been disposed according to an hexagonal pattern with distance corresponding to a 3 dB overlapping point at the beam triple intersection point. The resulting C/I probability density function4 (PDF) has been derived for the different frequency reuse factors and corresponding results are reported u2

+

v2

4 Assuming

= 1 = 09

all beams loaded with the same RF power.

in Fig. 5. As expected the frequency reuse 1 results in the widest C/I spreading range and in the minimum C/I value compared to less pushed frequency reuse schemes. The 20 GHz fade distribution selected for the study case is representative of a Mediterranean (center Italy) propagation impairment profile. The resulting fading Cumulative Distribution Function (CDF) is shown in Fig. 6. Fading attenuation over the satellite coverage region grid points have been generated according to this distribution as location independent random processes. The downlink traffic has been assumed uniformly distributed over a grid of about 14000 equi-spaced points.

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0

10 0.12

−1

10 0.1

−2

10

PDF

CDF

0.08 −3

10

0.06 −4

10 0.04

−5

10 0.02

−6

10 −35 0 −6

−2

0

2

4 C/I (dB)

6

8

10

12

−15

−10

−5

0

Capacity Results

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PDF

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0.05

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22

C/I (dB)

b) Frequency reuse factor 3 0.14

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−20

Fig. 6 CDF for the forward link fading: typical attenuation distribution for Nola (I).

0.35

0.06

0.04

0.02

0

−25

14

a) Frequency reuse factor 1.

0

−30

a (dB) −4

8

10

12

14

16 C/I (dB)

c) Frequency reuse factor 4.

Fig. 5 PDF for the forward link C/I

The normalized average beam capacity 5 calculation has been performed following the proposed ACM approach. The Ka-band satellite broadband system parameters are described in Table 1. The following results have been computed taking into account the physical layer parameters obtained from the efficiency optimization described in the previous section and random Ka-band fading attenuation generated at each location according to the CDF of Fig. 6. For the classical TDM case a frequency reuse 4 with a concatenated Reed Solomon (204,188) and r=2/3 convolutional FEC code according to the DVB-S standard 9 have been assumed requiring an E b =Nt : dB for QEF operations. As for classical TDM systems no downlink power control is adopted, it has been assumed a fixed fading margin of 3.9 dB corresponding to an outage probability of 99.5 % at the edge of coverage. Numerical results shown in Fig. 7 clearly indicate the large capacity gain provided by ACM compared to classical non power controlled TDM downlink. The reason for this remarkable ACM downlink capacity advantage is explained by the fact that current broadband systems are based on a worst-case physical layer sizing matching the worst-case C/I and propagation impairment that satisfy the required outage probability. As Fig. 5 indicates, C/I values over the satellite coverage region are subject to an important spread that can be readily exploited by the ACM adaptive physical layer. Similarly, propagation fading is

=57

5 By normalized we mean the average spectral efficiency in b/s/Hz/beam versus the RF power per Mcps. This normalization allows to make a fair comparison for different frequency reuse factors and to easily scale results to absolute average capacity and beam RF power.

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1

0.9

0.8

Efficiency (bit/sec/Hz/beam)

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0.7 ACM fr1 ACM fr3 ACM fr4 ACM fr4 with (C/I)oth ACM fr1 with (C/I)oth ACM fr3 with (C/I)oth fix QPSK DVB−S

0.6

0.5

0.4

0.3

0.2

0.1

0

0

0.025

0.05

0.075

0.1

0.125 0.15 P/B (W/Mcps)

0.175

0.2

0.225

0.25

Fig. 7 Simulated normalized average beam capacity as a function of the satellite RF power/Mcps

not counteracted by a static margin applied to all locations independently from their current propagation impairment situation. Finally, the physical layer adaptability allows to exploit a higher frequency reuse with the same satellite antenna design. Fig. 7 results show that as the ratio between the RF satellite transmitted power and the total bandwidth is increasing the link SNIR conditions allow higher spectral efficient modulations, so that the average capacity is improving until saturation is reached. In the present study case, frequency reuse 3 represents the optimum frequency reuse scheme. However this result will depend on the antenna design and in particular on the beam center spacing adopted. In Fig. 7 the average beam normalized capacity results obtained taking into account the degradation due to the intermodulation and cross-polar co-channel interference indicated with CI oth are also shown. It has been dB6 . It is apparent how the higher assumed CI oth

( ) ( ) = 15

6 Physical

layer simulation results indicate that for the 4+12 APSK modulation format7 with optimal TWTA operating point the in-band in-

the frequency reuse factor is the higher the capacity drop due to the CI oth factor. Consequently, the gap between frequency reuse 1 and 3 is remarkably reduced while between reuse 3 and 4 is increased. The increased ACM average normalized efficiency increase with respect to classical TDM systems is paid by the non constant TDM slot bit rate delivered over the coverage region due to the C/I location dependency and the propagation impairment time dependency. Further insight on this aspect can be gained looking at the bit rate distribution within the overall coverage region as it resulted from the system analysis. Results presented in Fig. 8 indicate that frequency reuse 1 slot bit rate range is the widest and includes both the smallest and the highest rate; on the contrary the frequency reuse 3 slot bit rate variability is limited to a factor two. However, the latter case has the highest average rate, about 355 Mbit/sec that for a 500 MHz total bandwidth corresponds to about 60 Gbps

( )

termodulation C=I is about 16 dB.

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with 32 dBW of satellite EIRP. This is a very remarkable results considering that for the same availability current TDM systems will provide about 20 Gbps for the same satellite total power and bandwidth. Additional simulation results not reported here for a more conventional 48 beams satellite covering Europe indicate a comparable but slightly higher efficiency increase due to ACM adoption in the downlink.

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600 Rb (Mbit/sec)

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1200

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350 400 Rb (Mbit/sec)

450

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b) Frequency reuse factor 3. 0.14

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a) Frequency reuse factor 1.

In this paper a new physical layer and link adaptation technique which consists in changing slot bit rate rather than power or frequency band to face location and timevarying propagation conditions has been investigated. The average efficiency has been analytically derived and numerical results have been shown in a study case of a future multibeam GEO next generation satellite system for multimedia applications. The remarkable capacity advantage (in the order of 300 %) with respect to classical TDM systems is due to the ACM capability of adapting to different link conditions by changing the physical layer parameters and consequently the user data rate. This adaptation is performed taking into account the result of an optimization process aiming at maximizing the efficiency of each single link. The variable packet delay time due to a non-constant delivered data rate over the satellite coverage can be partially or totally compensated by assigning the UT a variable number of time slots within the frame. Further work is currently on-going to extend the ACM analysis to the uplink of broadband multimedia satellite systems. Acknowledgments: The Authors are much grateful to Miss. A. Perez-Carro Rios for her support in the satellite antenna C/I simulations, to Mr. M. Sabbadini for his help in antenna modeling and to Dr. B. Arbesser-Rastburg and Mr. A. Martellucci for their inputs on propagation data.

Appendix Terminal Noise Temperature Modeling

0.06

0.04

0.02

0 150

200

250

300 350 Rb (Mbit/sec)

400

450

500

Here a classical approximation for deriving the receiver noise temperature dependence on the atmospheric attenuation is illustrated. By recalling that the noise temperature seen by the antenna T A is:

( )=aT

c) Frequency reuse factor 4.

Fig. 8 PDF for the forward link bit rate over the coverage P : (P dBW and Rc Mcps) region at B

= 0 025 = 10

= 400

TA a

SKY

+T

GND

+ T (1 m

a

)

(19)

where TSKY is the clear sky temperature, T GND is the ground temperature, T m is the propagation media average

8 OF 9 A MERICAN I NSTITUTE OF A ERONAUTICS AND A STRONAUTICS PAPER AIAA-2002-1863

attenuation and a is the attenuation. The total receiver input temperature is given by:

() = = T =4 T =4

TIN a

CS 0 0

( )+T + T (1 a) +T +T

TA a

RX

T0CS

0

TRX Tm

SKY

GND

TSKY

(20)

()

Therefore the noise power spectral density N 0 a at the receiver can be computed as:

( ) = KT (a) = =

N0 a

IN

+ K T (1 a) + N (1 a)

KT0CS N0CS

0

0

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(21) where K is the Boltzmann constant.

References 1 L.

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